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Evaluation of Tb response to snowpack by multiple microwave radiative transfer models Do Hyuk “DK” Kang NASA Goddard Space Flight Center NPP Program by.

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Presentation on theme: "Evaluation of Tb response to snowpack by multiple microwave radiative transfer models Do Hyuk “DK” Kang NASA Goddard Space Flight Center NPP Program by."— Presentation transcript:

1 Evaluation of Tb response to snowpack by multiple microwave radiative transfer models Do Hyuk “DK” Kang NASA Goddard Space Flight Center NPP Program by ORAU July 15 th 2015 NASA Postdoc Program NASA Goddard Space Flight Center

2 MEMLS, Mätzler and Wiesmann 1999 HUT, Pulliainen et al., 1999 DMRT, Tsang et al., 2007, Picard et al.,

3 Frolov and Marchert 1999, Hallikainen et al. 1986, TGRS

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5 Coupled Model Kang and Barros 2010 Matzler and Wiesmann 1999

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7 Coupled Model I : CLPX-1 Mass Balance Energy Balance

8 Coupled Model I : NoSREx-I II Mass Balance Energy Balance

9 CLPX

10 Schanda and Matzler 1981 Willis et al. 2012 RS and Env Kang et al. 2014 Published in IEEE

11 0.56 µm 36.5 GHz

12 Reflectivity discrepancy b/w microwave and visible/Infrared

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16 Figure- Horizontally polarized TB responses at AMSR-E frequencies such as 6.9, 10.7, 18.7, 23.8, 36.5, and 89.0 GHz, evaluated by MEMLS, HUT, and DMRT-Tsang with increasing snow grain sizes.

17 Q) Why MEMLS and HUT are fast saturated with the snow grain sizes at 18.7 GHz compared with the HUT and DMRT-Tsang?

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19 Q) Why DMRT-Tsang has a concave Tb response with snow grain sizes?

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22 Figure- Vertically polarized TB responses at AMSR-E frequencies such as 6.9, 10.7, 18.7, 23.8, 36.5, and 89.0 GHz, evaluated by MEMLS, HUT, and DMRT-Tsang with increasing snow density from 100 to 700 kg/m 3.

23 Q) Why all 3 RTMs have increases with increase of snow density at 89 GHz?

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25 z = epsaliceimag(fGHz,TK,Sppt) Q) Why all 3 RTMs have increasing curve with increase of snow density at 89 GHz?

26 Conclusions Forward model is a key to improve the inversion process for the earth features including snow Forward model can be decomposed to 1) snow physics and 2) RTM RTMs can be replaced with any model depending on a simulation of Tb, reflectivity, and scattering coefficient. 3 RTMs have been evaluated with gradual changes in snow physical properties

27 http://geosci.uchicago.edu/~rtp1/glaciers/EnergyBudget.html

28 Prerequisites Statics, Dynamics: force Fluid Mechanics: pressure, geometry, and flux Engineering Mathematics: eigenvalue solution, matrix inversion, and wave equation Electromagnetic Waves: polarization, multi-layer Signal Processing: low, high pass filters, FFT

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30 Top view of conical scan 30 Conical Scan rate: nominally 15 RPM, depends on altitude & airspeed for imaging without gaps Earth Incidence Angle 40 deg up from nadir Footprint size depends on altitude  Radar Min altitude 1500ft(457m): 200m dia.*  Radiometer Min alt 500ft(152m): 65m dia.*  Max altitude** 11000 ft(3353m): 1445m dia.  * geometric mean  ** 25000 ft if pressurized Full 360 deg scan yields 2 looks (fore & aft) of the surface 2 swath images (fore half-scan & aft half-scan) different fore vs. aft readings depending on target nature 12/5/2014Kim et al, SED seminar

31 Key Words Matzler and Wiesmann 1999 Devonec and Barros 2002 TbTb TsTs p ec freq LWC Brightness Temperature Absorption Coeffi. Scattering Coeffi. Real Permittivity Imaginary Permittivity

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38 Matzler and Wisemann 1999 RS and Env

39 Frolov and Marchert 1999, Hallikainen et al. 1986, TGRS

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42 Outline Concept: Radiative V.S. Snow Physical Variables Implementation: Coupled model between snow physics and forward model Application: Valdai Russia, CLPX 2002- 2003 Contribution: LWC & Snow grain size

43 Key Words Matzler and Wiesmann 1999 Devonec and Barros 2002 TbTb TsTs p ec freq LWC Brightness Temperature Absorption Coeffi. Scattering Coeffi. Real Permittivity Imaginary Permittivity

44 Matzler and Wisemann 1999 RS and Env

45 Model Setup State Variables (SWE [m], Snow depth [m], Snow density [kg/m 3 ], Snow Temperature [K], and Grain Size (will be) at each layer from 1st to nth layer 1-D Column simulation both for snow physics and radiation schemes with multi-layer Hourly Met. Data needed to drive model Output: Hourly Vertical Profiles of Snowpacks, Corresponding Tb [K], emissivity [ ], and Teff [K] Kang and Barros 2012 Part I and II

46 Site Descriptions Valdai, Russia, 78~83, SMMR, 25X25 km CLPX 2002-2003, 02~03, SSM/I, AMSR-E 25X25 km

47 Coupled Model I : Snow Physics Mass Balance Energy Balance

48 VALDAI

49 CLPX

50 Diurnal Cycle of Snow Physics Snow Temperature: Being tilted at 15:00 LST

51 Seasonal Cycle of Snow Physics Range of Snow Temperature and Density : Being narrowed in March 2003

52 Schanda and Matzler 1981 Willis et al. 2012 RS and Env Kang et al. 2012 Accepted in IEEE

53 Kang et al. 2012 Accepted in IEEE

54 Kang et al. 2012 Accepted in IEEE

55 Wiscomb and Warren 1980 VS Mätzler 2000 2997924 GHz = infrared 37 GHz = microwave

56 Ice-Lamellae Model (Mätzler 2000, DK imp.) Six flux theory: r, t, and e

57 Scattering: multi freq.

58 GPS + SNOTEL stations

59 Forward Simulators of Passive and Active Microwave.

60 Waveguide/free space method

61 Future Topics Grain size Ice lenses within snow layers Depth hoar/surface hoar First snow Intensity (radiative trnaser) Electric Dipole Moment Impedance Matching


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